On this talk we'll see how to do a disaster recovery from our dearest Kubernetes cluster and workloads. We'll review how Velero can help us on that and we'll show some hands on recovering a oh shit moment in our Kubernetes cluster.
A Series of Fortunate Events: Building an Operator in JavaVMware Tanzu
SpringOne 2021:
Session Title: A Series of Fortunate Events: Building an Operator in Java
Speakers: Alberto C. Ríos, Staff Engineer at VMware; Bella Bai, Software Engineer at VMware
Thoughts on heptio's ark - Contributors Meet 21st Sept 2018OpenEBS
Create a OpenEBS ARK Plugin that will implement the Block-Store API exposed by ARK
Backup Operation
ARK will invoke the Plugin-Snapshot (Backup) method.
Plugin: will call maya-apiserver backup api on a given volume
Maya-apiserver backup will call volumes (jiva/cstor) backup api
(jiva/cstor) volume controller will take a snapshot, and pass the request to one of the replica’s to push snapshot data to remote backup location (say S3 compatible -- as passed via the ark plugin or a custom backup location on mayaonline or may be a nfs server that openebs supports ). The code to actually push the data to backup location can make use of restic. We are putting it at the jiva/cstor for getting access to snapshot/incr snapshot data.
Restore Operation
ARK will invoke the Plugin-VolumeFromSnapshot (Restore) method
Plugin will invoke maya-apiserver to create a new PV/PVC and restore the data from backup.
ARK will launch the application with the PV/PVC.
This document provides instructions for installing Kubernetes on 3 VMs to create a multi-node Kubernetes cluster. It describes how to install Kubernetes master on the first VM, configure it with flannel networking, and join two additional VMs as worker nodes to the cluster. It also demonstrates installing Helm and common Kubernetes applications like Traefik, Rook, Prometheus, and Heapster.
On parle des Operator Kubernetes, mais de quoi s’agit-il ? Comment peut-on programmer son cluster Kubernetes et surtout, est-il possible de les écrire en Java ?
C’est ce que nous allons présenter au cours de 3 sessions dont celle-ci est la première. Dans cette session, nous allons présenter les différentes ressources de l’api REST de Kubernetes, les CRD (Custom Resource Definition), la bibliothèque fabric8 kubernetes-client et le projet exemple Hypnos.
par Charles Sabourdin
This document provides an introduction and overview of Kubernetes for deploying and managing containerized applications at scale. It discusses Kubernetes' key features like self-healing, dynamic scaling, networking and efficient resource usage. It then demonstrates setting up a Kubernetes cluster on AWS and deploying a sample application using pods, deployments and services. While Kubernetes provides many benefits, the document notes it requires battle-testing to be production-ready and other topics like logging, monitoring and custom autoscaling solutions would need separate discussions.
Amazon EKS Architecture in detail including CNI/Networking, IAM, Provisioning, Shared Responsibility Model, Project Calico, Load Balancing, Logging/Metrics, CI/CD using AWS CodePipeline, CodeCommit, CodeBuild, Lambda, Amazon ECR and Parameter Store and finally the use of Spot Instances which could yield a savings of 70-90% versus conventional on-demand EC2 instances.
The document provides an overview of Kubernetes architecture and components. It describes that a Kubernetes cluster contains a master node which manages container orchestration and worker nodes that run application containers. The master contains components like kube-apiserver, etcd, kube-scheduler and kube-controller-manager. Worker nodes run kubelet and kube-proxy. Kubernetes uses objects like pods, replica sets and deployments to define and manage application workloads across the cluster. Pods are the basic building blocks and controllers help ensure availability of pods.
This document discusses storage provisioning in Docker and Kubernetes environments. It covers Docker volume plugins, the container storage interface (CSI) specification, and persistent volume provisioning workflows in Kubernetes. Docker volume plugins allow storage providers to integrate with the Docker engine. CSI aims to standardize storage plugins across container orchestrators. Kubernetes uses persistent volumes, persistent volume claims, and storage classes to provision storage for pods. Considerations for high availability and different operating systems are also discussed.
A Series of Fortunate Events: Building an Operator in JavaVMware Tanzu
SpringOne 2021:
Session Title: A Series of Fortunate Events: Building an Operator in Java
Speakers: Alberto C. Ríos, Staff Engineer at VMware; Bella Bai, Software Engineer at VMware
Thoughts on heptio's ark - Contributors Meet 21st Sept 2018OpenEBS
Create a OpenEBS ARK Plugin that will implement the Block-Store API exposed by ARK
Backup Operation
ARK will invoke the Plugin-Snapshot (Backup) method.
Plugin: will call maya-apiserver backup api on a given volume
Maya-apiserver backup will call volumes (jiva/cstor) backup api
(jiva/cstor) volume controller will take a snapshot, and pass the request to one of the replica’s to push snapshot data to remote backup location (say S3 compatible -- as passed via the ark plugin or a custom backup location on mayaonline or may be a nfs server that openebs supports ). The code to actually push the data to backup location can make use of restic. We are putting it at the jiva/cstor for getting access to snapshot/incr snapshot data.
Restore Operation
ARK will invoke the Plugin-VolumeFromSnapshot (Restore) method
Plugin will invoke maya-apiserver to create a new PV/PVC and restore the data from backup.
ARK will launch the application with the PV/PVC.
This document provides instructions for installing Kubernetes on 3 VMs to create a multi-node Kubernetes cluster. It describes how to install Kubernetes master on the first VM, configure it with flannel networking, and join two additional VMs as worker nodes to the cluster. It also demonstrates installing Helm and common Kubernetes applications like Traefik, Rook, Prometheus, and Heapster.
On parle des Operator Kubernetes, mais de quoi s’agit-il ? Comment peut-on programmer son cluster Kubernetes et surtout, est-il possible de les écrire en Java ?
C’est ce que nous allons présenter au cours de 3 sessions dont celle-ci est la première. Dans cette session, nous allons présenter les différentes ressources de l’api REST de Kubernetes, les CRD (Custom Resource Definition), la bibliothèque fabric8 kubernetes-client et le projet exemple Hypnos.
par Charles Sabourdin
This document provides an introduction and overview of Kubernetes for deploying and managing containerized applications at scale. It discusses Kubernetes' key features like self-healing, dynamic scaling, networking and efficient resource usage. It then demonstrates setting up a Kubernetes cluster on AWS and deploying a sample application using pods, deployments and services. While Kubernetes provides many benefits, the document notes it requires battle-testing to be production-ready and other topics like logging, monitoring and custom autoscaling solutions would need separate discussions.
Amazon EKS Architecture in detail including CNI/Networking, IAM, Provisioning, Shared Responsibility Model, Project Calico, Load Balancing, Logging/Metrics, CI/CD using AWS CodePipeline, CodeCommit, CodeBuild, Lambda, Amazon ECR and Parameter Store and finally the use of Spot Instances which could yield a savings of 70-90% versus conventional on-demand EC2 instances.
The document provides an overview of Kubernetes architecture and components. It describes that a Kubernetes cluster contains a master node which manages container orchestration and worker nodes that run application containers. The master contains components like kube-apiserver, etcd, kube-scheduler and kube-controller-manager. Worker nodes run kubelet and kube-proxy. Kubernetes uses objects like pods, replica sets and deployments to define and manage application workloads across the cluster. Pods are the basic building blocks and controllers help ensure availability of pods.
This document discusses storage provisioning in Docker and Kubernetes environments. It covers Docker volume plugins, the container storage interface (CSI) specification, and persistent volume provisioning workflows in Kubernetes. Docker volume plugins allow storage providers to integrate with the Docker engine. CSI aims to standardize storage plugins across container orchestrators. Kubernetes uses persistent volumes, persistent volume claims, and storage classes to provision storage for pods. Considerations for high availability and different operating systems are also discussed.
This document provides instructions for getting started with Kubernetes on AWS. It discusses initial cluster setup using a CloudFormation template, checking cluster values, adding nodes, deploying applications using YAML files, scaling deployments, updating applications, and using tools like kops for production Kubernetes cluster setup. The document emphasizes that tools can help manage complex Kubernetes infrastructure and that high availability in Kubernetes involves running multiple clusters across Availability Zones rather than a single multi-AZ cluster.
This is the second session of Deep Dive into Kubernetes. It includes information on optimizing Docker image size, persistent volumes, container security, and different aspects of running Kubernetes on GKE and AWS.
A brief study on Kubernetes and its componentsRamit Surana
Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. Using the concepts of "labels" and "pods", it groups the containers which make up an application into logical units for easy management and discovery.
The document provides an overview of the logical architecture of Kubernetes. It describes the main components that make up the Kubernetes control plane (API server, scheduler, etc.) and Kubernetes workers, as well as core Kubernetes objects like pods, replica sets, deployments, services, ingress and configmaps/secrets. It also touches on controllers, operators, Kubernetes manifests and provides an example manifest configuration.
We will use a traditional slave/master set up with asynchronous replication, configurable replication, depending on user configuration, and no requirement for a constant connection.
This document provides an overview of OpenStack Compute (Nova), which is an open source software that provides infrastructure as a service cloud computing capabilities. It discusses how Nova controls virtual machine instances, networks, and access through users and projects similar to Amazon EC2. Nova exposes these capabilities through APIs for developers and interfaces for administrators. Key components of Nova like nova-compute, nova-scheduler, nova-api and message queue are described along with their functions and communication processes. Several Nova API examples are listed with their use cases, expected return codes and outcomes. Process flow diagrams are included for creating a server, attaching a volume, and detaching a volume to illustrate the component interactions.
Kubernetes seems to be the biggest buzz word currently in the DevOps world. The Google designed container orchestrator based in their 10+ years of experience running production applications using containers seems to have positioned as the market leader.
Open source, available in both Google Cloud and Azure container platforms or as a custom installation, it is ready to receive production loads.
During this talk we will discover how does Kubernetes works, its architecture, what components compose a Kubernetes cluster. We will also learn what objects can a developer use to deploy its applications on a Kubernetes cluster. We will see a live demo where we will deploy an application and then introduce changes to it without any downtime.
This document provides an overview of Kubernetes including:
1) Kubernetes is an open-source platform for automating deployment, scaling, and operations of containerized applications. It provides container-centric infrastructure and allows for quickly deploying and scaling applications.
2) The main components of Kubernetes include Pods (groups of containers), Services (abstract access to pods), ReplicationControllers (maintain pod replicas), and a master node running key components like etcd, API server, scheduler, and controller manager.
3) The document demonstrates getting started with Kubernetes by enabling the master on one node and a worker on another node, then deploying and exposing a sample nginx application across the cluster.
Kubernetes is an open-source tool for managing containerized applications across clusters of nodes. It provides capabilities for deployment, maintenance, and scaling of applications. The document discusses Kubernetes concepts like pods, deployments, services, namespaces and components like the API server, scheduler and kubelet. It also covers Kubernetes commands and configuration using objects like config maps, secrets, volumes and labels.
Prometheus was recently accepted into the Cloud Native Computing Foundation, making it the second project after Kubernetes to be given their blessing and acknowledging that Prometheus and Kubernetes make an awesome combination. In this talk we'll cover common patterns for running Prometheus on Kubernetes, how to monitor services on Kubernetes, and some cool tips and hacks to ensure you get the most out of your Prometheus + Kubernetes deployment.
The document provides an overview of Azure Kubernetes Service (AKS) including:
- AKS simplifies deployment, management, scaling and monitoring of containerized applications on Kubernetes.
- AKS uses a master-worker node architecture with master nodes managing the cluster state and worker nodes running application containers.
- Key AKS concepts include clusters, pods, deployments, replica sets, and services.
- The AKS architecture includes etcd, kube-apiserver, controller manager, kube-scheduler and cloud controller manager on the master node, and kubelet, container runtime and kube-proxy on worker nodes.
- Applications can be deployed to AKS through Kubernetes manifest
kubernetes is a provision and orchestration tool. It is used automating app deployments. It can be used easily scaling the deployments. It's self healing natures makes the process of application deployment and maintenance easier.
Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. The tool has the facility to seamelessly upgrade the deployment versions. Kubernetes is a portable, extensible, open source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.
Containers are similar to VMs, but they have relaxed isolation properties to share the Operating System (OS) among the applications. Therefore, containers are considered lightweight. Similar to a VM, a container has its own filesystem, share of CPU, memory, process space, and more. As they are decoupled from the underlying infrastructure, they are portable across clouds and OS distributions.
Containers have become popular because they provide extra benefits, such as:
Agile application creation and deployment: increased ease and efficiency of container image creation compared to VM image use.
Continuous development, integration, and deployment: provides for reliable and frequent container image build and deployment with quick and efficient rollbacks (due to image immutability).
Dev and Ops separation of concerns: create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure.
Observability: not only surfaces OS-level information and metrics, but also application health and other signals.
Environmental consistency across development, testing, and production: runs the same on a laptop as it does in the cloud.
Cloud and OS distribution portability: runs on Ubuntu, RHEL, CoreOS, on-premises, on major public clouds, and anywhere else.
Application-centric management: raises the level of abstraction from running an OS on virtual hardware to running an application on an OS using logical resources.
Loosely coupled, distributed, elastic, liberated micro-services: applications are broken into smaller, independent pieces and can be deployed and managed dynamically – not a monolithic stack running on one big single-purpose machine.
Resource isolation: predictable application performance.
Resource utilization: high efficiency and density. Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. Kubernetes provides you with:
Service discovery and load
Create a Varnish cluster in Kubernetes for Drupal caching - DrupalCon North A...Ovadiah Myrgorod
Varnish is a caching proxy usually used for high profile Drupal sites. However, configuring Varnish is not an easy task that requires a lot of work. It is even more difficult when it comes to creating a scalable cluster of Varnish nodes.
Fortunately, there is a solution. I’ve been working on kube-httpcache project (https://github.com/mittwald/kube-httpcache) that takes care of many things such as routing, scaling, broadcasting, config-reloading, etc...
If you need to run more than one instance of Varnish, this session is for you. You will learn how to:
* Launch a single instance of Varnish in Kubernetes.
* Configure Varnish for Drupal.
* Scale Varnish from 1 to N nodes as part of the cluster.
* Make your Varnish cluster resilient.
* Reload Varnish configs on the fly.
* Properly invalidate cache for multiple Varnish nodes.
This session requires some basic understanding of Docker and Kubernetes; however, I will provide some intro if you are new to it.
Join this session and enjoy!
Appsecco Kubernetes Hacking Masterclass. The slides used during the class with links to the commands, scripts and setup information.
These slides are to be used with the masterclass video recording on YouTube -
Hands on exercises are highly recommended to get the most out of this class!
Kubernetes - Using Persistent Disks with WordPress and MySQLpratik rathod
Use Kubernetes as a persistent disk to avoid killed services in PHP, WordPress or any web module using Google cloud platform. We use this open source container cluster manager to deploy CMS like WordPress and database server like MySQL.
Veritas NetBackup 7.6 benchmark comparison: Data protection in a large-scale ...Principled Technologies
In an enterprise environment, a data center VM footprint can grow quickly; large-scale deployments of thousands of virtual machines are becoming increasingly common. Risk of failure grows proportionally to the number of systems deployed and critical failures are unavoidable. Your ability to offer data protection from a backup solution is critical to business continuity. Elongated, inefficient protection windows can create resource contention with production environments, making it critical to execute system backup in a finite window of time.
The Veritas NetBackup Integrated Appliance running NetBackup 7.6 offered application protection to 1,000 VMs in 67.3 percent less time in SAN testing and used NetApp array-based snapshots to create recovery points in 54.1 percent less time than Competitor “V.” NetBackup was able to perform application-consistent backups at 1,000 VMs while Competitor “V” started to fail as the environment approached 300 VMs. Also, Competitor “V” was not able to complete a concurrent restore of 24 VMs while Veritas NetBackup was. The ability to complete backups and recoveries at scale are the most critical factor when determining the right solution for you. These time savings can scale as your VM footprint grows, allowing you to execute both system protection and user-friendly, simplified recovery.
This document provides an overview and instructions for setting up and managing infrastructure and applications on Amazon EC2 Container Service (ECS). It covers the key components of ECS including tasks, containers, clusters and container instances. It also discusses setting up ECS infrastructure with CloudFormation, monitoring with CloudWatch, service discovery with Route 53 and Weaveworks, security with IAM roles and policies and image scanning. The document demonstrates deploying applications to ECS including scheduling containers for batch jobs and long-running apps. It shows automating deployments with Jenkins and Shippable and using platform as a service options like Elastic Beanstalk, Convox and Remind Empire. Finally, it provides instructions for using the ECS CLI
The document provides instructions for using the FIWARE LAB Cloud Portal to deploy virtual machines and applications. It describes how to create an account, launch VM instances, configure security groups and keypairs, take snapshots, use object storage, and connect to instances. The portal is based on the OpenStack cloud computing platform.
Gianluca Arbezzano Wordpress: gestione delle installazioni e scalabilità con ...Codemotion
Gianluca Arbezzano discusses using Docker and related technologies to scale WordPress deployments. Docker provides isolation and security while allowing workloads to scale horizontally across multiple servers. Elastic Container Service on AWS further simplifies management by allowing containers to be orchestrated across a cluster of EC2 instances and auto-scaled based on demand. HAProxy can also help load balance traffic between containers for high availability.
This talk is a journey through the wonders and mysteries of Kubernetes namespaces. While being a known feature of Kubernetes, there are a number of not so well known things to know about them that can teach a lot about Kubernetes. During the talk we will not only take a look at the details of Kubernetes namespaces, but also show how they are used in different production scenarios.
Tu non puoi passare! Policy compliance con OPA Gatekeeper | Niccolò RaspaKCDItaly
Per una buona gestione di un cluster Kubernetes in contesti di produzione è necessaria l’introduzione di policy per validare le risorse create all’interno del cluster.
More Related Content
Similar to Kubernetes Backup and Migration Strategies with Velero | Ramiro Alvarez Fernandez
This document provides instructions for getting started with Kubernetes on AWS. It discusses initial cluster setup using a CloudFormation template, checking cluster values, adding nodes, deploying applications using YAML files, scaling deployments, updating applications, and using tools like kops for production Kubernetes cluster setup. The document emphasizes that tools can help manage complex Kubernetes infrastructure and that high availability in Kubernetes involves running multiple clusters across Availability Zones rather than a single multi-AZ cluster.
This is the second session of Deep Dive into Kubernetes. It includes information on optimizing Docker image size, persistent volumes, container security, and different aspects of running Kubernetes on GKE and AWS.
A brief study on Kubernetes and its componentsRamit Surana
Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. Using the concepts of "labels" and "pods", it groups the containers which make up an application into logical units for easy management and discovery.
The document provides an overview of the logical architecture of Kubernetes. It describes the main components that make up the Kubernetes control plane (API server, scheduler, etc.) and Kubernetes workers, as well as core Kubernetes objects like pods, replica sets, deployments, services, ingress and configmaps/secrets. It also touches on controllers, operators, Kubernetes manifests and provides an example manifest configuration.
We will use a traditional slave/master set up with asynchronous replication, configurable replication, depending on user configuration, and no requirement for a constant connection.
This document provides an overview of OpenStack Compute (Nova), which is an open source software that provides infrastructure as a service cloud computing capabilities. It discusses how Nova controls virtual machine instances, networks, and access through users and projects similar to Amazon EC2. Nova exposes these capabilities through APIs for developers and interfaces for administrators. Key components of Nova like nova-compute, nova-scheduler, nova-api and message queue are described along with their functions and communication processes. Several Nova API examples are listed with their use cases, expected return codes and outcomes. Process flow diagrams are included for creating a server, attaching a volume, and detaching a volume to illustrate the component interactions.
Kubernetes seems to be the biggest buzz word currently in the DevOps world. The Google designed container orchestrator based in their 10+ years of experience running production applications using containers seems to have positioned as the market leader.
Open source, available in both Google Cloud and Azure container platforms or as a custom installation, it is ready to receive production loads.
During this talk we will discover how does Kubernetes works, its architecture, what components compose a Kubernetes cluster. We will also learn what objects can a developer use to deploy its applications on a Kubernetes cluster. We will see a live demo where we will deploy an application and then introduce changes to it without any downtime.
This document provides an overview of Kubernetes including:
1) Kubernetes is an open-source platform for automating deployment, scaling, and operations of containerized applications. It provides container-centric infrastructure and allows for quickly deploying and scaling applications.
2) The main components of Kubernetes include Pods (groups of containers), Services (abstract access to pods), ReplicationControllers (maintain pod replicas), and a master node running key components like etcd, API server, scheduler, and controller manager.
3) The document demonstrates getting started with Kubernetes by enabling the master on one node and a worker on another node, then deploying and exposing a sample nginx application across the cluster.
Kubernetes is an open-source tool for managing containerized applications across clusters of nodes. It provides capabilities for deployment, maintenance, and scaling of applications. The document discusses Kubernetes concepts like pods, deployments, services, namespaces and components like the API server, scheduler and kubelet. It also covers Kubernetes commands and configuration using objects like config maps, secrets, volumes and labels.
Prometheus was recently accepted into the Cloud Native Computing Foundation, making it the second project after Kubernetes to be given their blessing and acknowledging that Prometheus and Kubernetes make an awesome combination. In this talk we'll cover common patterns for running Prometheus on Kubernetes, how to monitor services on Kubernetes, and some cool tips and hacks to ensure you get the most out of your Prometheus + Kubernetes deployment.
The document provides an overview of Azure Kubernetes Service (AKS) including:
- AKS simplifies deployment, management, scaling and monitoring of containerized applications on Kubernetes.
- AKS uses a master-worker node architecture with master nodes managing the cluster state and worker nodes running application containers.
- Key AKS concepts include clusters, pods, deployments, replica sets, and services.
- The AKS architecture includes etcd, kube-apiserver, controller manager, kube-scheduler and cloud controller manager on the master node, and kubelet, container runtime and kube-proxy on worker nodes.
- Applications can be deployed to AKS through Kubernetes manifest
kubernetes is a provision and orchestration tool. It is used automating app deployments. It can be used easily scaling the deployments. It's self healing natures makes the process of application deployment and maintenance easier.
Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. The tool has the facility to seamelessly upgrade the deployment versions. Kubernetes is a portable, extensible, open source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.
Containers are similar to VMs, but they have relaxed isolation properties to share the Operating System (OS) among the applications. Therefore, containers are considered lightweight. Similar to a VM, a container has its own filesystem, share of CPU, memory, process space, and more. As they are decoupled from the underlying infrastructure, they are portable across clouds and OS distributions.
Containers have become popular because they provide extra benefits, such as:
Agile application creation and deployment: increased ease and efficiency of container image creation compared to VM image use.
Continuous development, integration, and deployment: provides for reliable and frequent container image build and deployment with quick and efficient rollbacks (due to image immutability).
Dev and Ops separation of concerns: create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure.
Observability: not only surfaces OS-level information and metrics, but also application health and other signals.
Environmental consistency across development, testing, and production: runs the same on a laptop as it does in the cloud.
Cloud and OS distribution portability: runs on Ubuntu, RHEL, CoreOS, on-premises, on major public clouds, and anywhere else.
Application-centric management: raises the level of abstraction from running an OS on virtual hardware to running an application on an OS using logical resources.
Loosely coupled, distributed, elastic, liberated micro-services: applications are broken into smaller, independent pieces and can be deployed and managed dynamically – not a monolithic stack running on one big single-purpose machine.
Resource isolation: predictable application performance.
Resource utilization: high efficiency and density. Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. Kubernetes provides you with:
Service discovery and load
Create a Varnish cluster in Kubernetes for Drupal caching - DrupalCon North A...Ovadiah Myrgorod
Varnish is a caching proxy usually used for high profile Drupal sites. However, configuring Varnish is not an easy task that requires a lot of work. It is even more difficult when it comes to creating a scalable cluster of Varnish nodes.
Fortunately, there is a solution. I’ve been working on kube-httpcache project (https://github.com/mittwald/kube-httpcache) that takes care of many things such as routing, scaling, broadcasting, config-reloading, etc...
If you need to run more than one instance of Varnish, this session is for you. You will learn how to:
* Launch a single instance of Varnish in Kubernetes.
* Configure Varnish for Drupal.
* Scale Varnish from 1 to N nodes as part of the cluster.
* Make your Varnish cluster resilient.
* Reload Varnish configs on the fly.
* Properly invalidate cache for multiple Varnish nodes.
This session requires some basic understanding of Docker and Kubernetes; however, I will provide some intro if you are new to it.
Join this session and enjoy!
Appsecco Kubernetes Hacking Masterclass. The slides used during the class with links to the commands, scripts and setup information.
These slides are to be used with the masterclass video recording on YouTube -
Hands on exercises are highly recommended to get the most out of this class!
Kubernetes - Using Persistent Disks with WordPress and MySQLpratik rathod
Use Kubernetes as a persistent disk to avoid killed services in PHP, WordPress or any web module using Google cloud platform. We use this open source container cluster manager to deploy CMS like WordPress and database server like MySQL.
Veritas NetBackup 7.6 benchmark comparison: Data protection in a large-scale ...Principled Technologies
In an enterprise environment, a data center VM footprint can grow quickly; large-scale deployments of thousands of virtual machines are becoming increasingly common. Risk of failure grows proportionally to the number of systems deployed and critical failures are unavoidable. Your ability to offer data protection from a backup solution is critical to business continuity. Elongated, inefficient protection windows can create resource contention with production environments, making it critical to execute system backup in a finite window of time.
The Veritas NetBackup Integrated Appliance running NetBackup 7.6 offered application protection to 1,000 VMs in 67.3 percent less time in SAN testing and used NetApp array-based snapshots to create recovery points in 54.1 percent less time than Competitor “V.” NetBackup was able to perform application-consistent backups at 1,000 VMs while Competitor “V” started to fail as the environment approached 300 VMs. Also, Competitor “V” was not able to complete a concurrent restore of 24 VMs while Veritas NetBackup was. The ability to complete backups and recoveries at scale are the most critical factor when determining the right solution for you. These time savings can scale as your VM footprint grows, allowing you to execute both system protection and user-friendly, simplified recovery.
This document provides an overview and instructions for setting up and managing infrastructure and applications on Amazon EC2 Container Service (ECS). It covers the key components of ECS including tasks, containers, clusters and container instances. It also discusses setting up ECS infrastructure with CloudFormation, monitoring with CloudWatch, service discovery with Route 53 and Weaveworks, security with IAM roles and policies and image scanning. The document demonstrates deploying applications to ECS including scheduling containers for batch jobs and long-running apps. It shows automating deployments with Jenkins and Shippable and using platform as a service options like Elastic Beanstalk, Convox and Remind Empire. Finally, it provides instructions for using the ECS CLI
The document provides instructions for using the FIWARE LAB Cloud Portal to deploy virtual machines and applications. It describes how to create an account, launch VM instances, configure security groups and keypairs, take snapshots, use object storage, and connect to instances. The portal is based on the OpenStack cloud computing platform.
Gianluca Arbezzano Wordpress: gestione delle installazioni e scalabilità con ...Codemotion
Gianluca Arbezzano discusses using Docker and related technologies to scale WordPress deployments. Docker provides isolation and security while allowing workloads to scale horizontally across multiple servers. Elastic Container Service on AWS further simplifies management by allowing containers to be orchestrated across a cluster of EC2 instances and auto-scaled based on demand. HAProxy can also help load balance traffic between containers for high availability.
Similar to Kubernetes Backup and Migration Strategies with Velero | Ramiro Alvarez Fernandez (20)
This talk is a journey through the wonders and mysteries of Kubernetes namespaces. While being a known feature of Kubernetes, there are a number of not so well known things to know about them that can teach a lot about Kubernetes. During the talk we will not only take a look at the details of Kubernetes namespaces, but also show how they are used in different production scenarios.
Tu non puoi passare! Policy compliance con OPA Gatekeeper | Niccolò RaspaKCDItaly
Per una buona gestione di un cluster Kubernetes in contesti di produzione è necessaria l’introduzione di policy per validare le risorse create all’interno del cluster.
Kubernetes Policy As Code usando WebAssembly | Flavio CastelliKCDItaly
Mettere in sicurezza un cluster Kubernetes richiede l'uso di diverse strategie e di strumenti per attuarle.
Tra queste, i Dynamic Admission Controllers giocano un ruolo fondamentale per garantire non solo la sicurezza di un cluster, ma anche la sua compliance. Infatti tramite di essi è possibile definire, ed applicare, regole personalizzate.
Nonostante molte organizzazioni riconoscano l'importanza di abbracciare la "filosofia" Policy As Code, sono purtroppo poche le realtà in cui questa metodologia viene utilizzata in ambienti di produzione.
Durante questo talk mostrerò come WebAssembly, una tecnologia nata originariamente per il Web, possa essere utilizzato per implementare strategie di Policy As Code in Kubernetes.
Vedremo come l'adozione di WebAssembly semplifichi il processo di creazione, mantenimento e distribuzione di queste policy.
Anche lo sviluppo del software ha un impatto importante sul clima e sull’ambiente.
Qualche esempio?
I Bitcoin producono tra 22 e 22.9 milioni di tonnellate di anidride carbonica all’anno
Minecraft, il videogioco più giocato al mondo, ha prodotto nella sua vita 600 milioni di kg di CO2
Gli sviluppatori che hanno realizzato questi software non pensavano di avere un impatto così importante sul clima mondiale.
Ora, però, è il momento di pensarci per il futuro.
Per questo ho realizzato kube-green, un progetto OSS su GitHub che ha l’obiettivo di ridurre la carbon footprint di applicativi Cloud Native.
In questo talk vedremo come funziona, una live demo e la sua roadmap per avere un mondo sempre più pulito e un software funzionante e scalabile.
Cloud Native resiliency patterns from the ground up | Ana-Maria MihalceanuKCDItaly
"Delay is the deadliest form of denial." C. Northcote Parkinson
We live in times when an application or service lag of even 2 seconds can be too long. Building a reliable Cloud Native distributed system means preventing failures and minimizing their effects to keep the system stable.
Join me to explore graceful recovery from unexpected scenarios using live coded examples of the well-known circuit breaker and retry patterns at the application level and complement those in the infrastructure (Kubernetes) with service discovery, load balancing, and load shedding patterns.
Serverless is a good pattern when it comes to saving infrastructure resources: why should you run apps when there’s nothing to do? The open source project Knative is often used to run functions as serverless apps in Kubernetes clusters.
In this talk, you’ll see how to leverage Knative for Kubernetes apps, not only functions. Check out how to apply serverless patterns to an existing Spring Boot / Nodejs app (backend / frontend) with a live demo.
Multi-Clusters Made Easy with Liqo: Getting Rid of Your Clusters Keeping Them...KCDItaly
Many companies are experiencing a dramatic increase in the number of their Kubernetes clusters, for
reasons such as geographical/legislative constraints, data/service replication, etc.
However, when the number of clusters increases, the complexity of deploying apps, managing the entire
multi-cluster infrastructure, and keeping its state under control, becomes rapidly an unmanageable
problem.
A possible solution is Liqo, an open-source project that simplifies the creation of multi-cluster topologies
by replicating the Kubernetes “cattle” model also to clusters.
Liqo creates a virtual cluster that spans multiple real clusters, either on-prem or managed (AKS, EKS,
GKE), and instantiates the desired applications seamlessly in the appropriate cluster.
This talk will discuss the potentials and roadblocks of this vision and highlight how Liqo brings multi-
cluster transparency to the users.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
7. Using the Velero CLI, the user creates a Backup
custom resource using the Kubernetes API. The
instruction accept filtering by namespace, resource or
labelling, for instance `velero backup create cluster
--include-namespace ghost --wait`.
01
The Velero Controller notice about the new Backup
resource and validated the command.
The Velero Controller starts the backup process. It
queries the Kubernetes API to backup the resources.
The Velero Controller push the backup file to a cloud
object storage. Besides, it creates snapshots using
the cloud Snapshot API of any existing PV. The
backup process finished after upload the file to the
cloud object storage.
Using the Velero CLI, the user creates a
Restore custom restore using the Kubernetes
API. The instruction accept filtering by
namespace, resource or labelling, for instance
to restore from the sample above `velero
restore create --from-backup cluster
--include-namespace ghost`.
The Velero Controller notices about the new
Restore resource, validates the command and
start pulling the data from the cloud object
storage.
02
03
04
05 06
The Velero Controller restores the resources
querying the Kubernetes API to restore the
resources. The restore process finished after
deploying the pull data to the Kubernetes API.
07
01
KUBERNETES CLUSTER
VELERO WORKFLOW
GENERIC DIAGRAM
CREATE BACKUP
RESOURCE LIST RESOURCES PUSH BACKUP DATA
BACKUP
PULL BACKUP DATA
04
05
RESTORE
02
CREATE RESTORE
RESOURCE RESTORE RESOURCES
KUBERNETES CLUSTER
api
07
api
VELERO SERVER
CONTROLLER
03
VELERO SERVER
CONTROLLER
06
9. VELERO WORKFLOW
DISASTER RECOVERY
Using the Velero CLI, the user creates a Backup custom
resource on EKS Cluster 1 using the Kubernetes API. The
instruction accept filtering by namespace, resource or
labelling, for instance `velero backup create cluster1
--include-namespace ghost --wait`.
01
The Velero Controller notice about the new Backup
resource and validated the command.
The Velero Controller starts the backup process. It
queries the Kubernetes API to backup the resources.
The Velero Controller push the backup file to a cloud
object storage. Besides, it creates snapshots using
the cloud Snapshot API of any existing PV. The
backup process finished after upload the file to the
cloud object storage.
Using the Velero CLI, the user creates a
Restore custom restore on EKS Cluster 2 using
the Kubernetes API. The instruction accept
filtering by namespace, resource or labelling,
for instance to restore from the sample above
`velero restore create --from-backup cluster1
--include-namespace ghost`.
The Velero Controller notices about the new
Restore resource, validates the command and start
pulling the data from the cloud object storage.
02
03
04
05 06
The Velero Controller restores the resources
querying the Kubernetes API to restore the
resources. The restore process finished after
deploying the pull data to the Kubernetes API. Data
from cluster1 has been recovered on cluster2.
07
01
05
BACKUP
RESTORE
EKS KUBERNETES CLUSTER 1
CREATE BACKUP
RESOURCE LIST RESOURCES PUSH BACKUP DATA
PULL BACKUP DATA
04
02
CREATE RESTORE
RESOURCE RESTORE RESOURCES
EKS KUBERNETES CLUSTER 2
api
07
api
VELERO SERVER
CONTROLLER
03
VELERO SERVER
CONTROLLER
06
10. VELERO WORKFLOW
DATA MIGRATION
Using the Velero CLI, the user creates a Backup custom
resource on EKS Cluster2 using the Kubernetes API.
The instruction accept filtering by namespace, resource
or labelling, for instance `velero backup create cluster2
--include-namespace ghost --wait`.
01
The Velero Controller notice about the new Backup
resource and validated the command.
The Velero Controller starts the backup process. It
queries the Kubernetes API to backup the resources.
Velero ensures a restic repository exists for the pod's
namespace. Velero creates a PodVolumeBackup
custom resource per volume listed in the pod
annotation. The main Velero process waits for the
PodVolumeBackup resources to complete or fail.
The Velero Controller push the backup file to a cloud
object storage. This file would be used for restores.
Using the Velero CLI, the user creates a
Restore custom restore on GKE cluster3 using
the Kubernetes API. The instruction accept
filtering by namespace, resource or labelling,
for instance to restore from the sample above
`velero restore create --from-backup cluster2
--include-namespace ghost`.
The Velero Controller notices about the new Restore
resource, validates the command and start pulling the
data from the cloud object storage. Velero creates a
PodVolumeRestore custom resource for each volume
to be restored in the pod.
02
03 04
05
06
The Velero Controller waits for each PodVolumeRestore
resource to complete or fail. It restores the resources
querying the Kubernetes API to restore the resources.
The restore process finished after deploying the pull data
to the Kubernetes API.
07
01
05
BACKUP
RESTORE
EKS KUBERNETES CLUSTER 2
CREATE BACKUP
RESOURCE PUSH BACKUP DATA
PULL BACKUP DATA
04
02
CREATE RESTORE
RESOURCE RESTORE RESOURCES
GKE KUBERNETES CLUSTER 3
api
07
api
VELERO SERVER
CONTROLLER
03
RESTIC
DAEMONSET
VELERO SERVER
CONTROLLER
06
RESTIC
DAEMONSET